Evidence map›Paper›PMID 41953269›Full record

ArticleIEEE sensors journal2025

Power Optimization of TENGs via Load Capacitance Sizing.

Maryam Hosseini, Mahmood Chahari, Milutin Stanacevic, Shahrzad Towfighian, Ryan Willing, Emre Salman

Abstract read
In one paragraph

Article in IEEE sensors journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. State-of-the-Art Power Transfer Methods in Triboelectric Energy Harvesters.IEEE circuits and systems magazine (New York, N.Y. : 2001)
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Maryam HosseiniDepartment of Electrical and Computer Engineering, Stony Brook University (SUNY), Stony Brook, NY 11794 USA.
Mahmood ChahariDepartment of Mechanical Engineering, Binghamton University, Binghamton, NY 13902 USA.
Milutin StanacevicDepartment of Electrical and Computer Engineering, Stony Brook University (SUNY), Stony Brook, NY 11794 USA.
Shahrzad TowfighianDepartment of Mechanical Engineering, Binghamton University, Binghamton, NY 13902 USA.
Ryan WillingDepartment of Mechanical and Materials Engineering, University of Western Ontario, London, ON N6A 3K7, Canada.
Emre SalmanDepartment of Electrical and Computer Engineering, Stony Brook University (SUNY), Stony Brook, NY 11794 USA.

Funding

Self-Powered Load Sensors for Total Knee Replacement Health MonitoringR01AR080798 · NIAMS · STATE UNIVERSITY OF NY,BINGHAMTON · PI Shahrzad Towfighian · 2022 to 2026
$2.2M
NIAMS NIH HHS R01 AR080798
6 · The paper itself

Abstract

A power optimization strategy is described for triboelectric energy harvesting systems by optimizing the load capacitor size within a full wave rectifier (FWR). In AC harvesters such as triboelectric nanogenerators (TENGs) with an FWR, the average power delivered to the rectifier increases in each cycle, ultimately reaching a steady state determined by system parameters. Through cycle-level analysis of input voltage, current, and rectifier turn-on time during mechanical motion, an optimal load capacitance is identified that maximizes power delivery while minimizing transient time to reach this maximum power. This approach achieves peak power delivery via capacitor sizing alone, eliminating the need for additional circuitry. Experimental results using a vertical contact-separation triboelectric nanogenerator with internal capacitance varying from 24pF to 96pF demonstrate that the optimal rectifier capacitance of 390pF achieves maximum power delivery (900nW at 1.7Hz and 2.7

Indexed as

Energy harvesting (EH)power optimizationTENGtriboelectric energy harvester

Identifiers

PMID41953269
PMCPMC13055921

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.